Globally, the patterns are coherent, with hot-spots for a given pattern appearing in a few spatially extensive and plausibly similar meteorological regimes. This coherence supports the hypothesis that the subjective patterns are associated with meaningful and distinct physical processes. Though the combination of crowd-sourced labels and deep learning helped answering many of the questions raised at the outset of this study it also raises some new ones, for instance whether important cloud regimes are missing from our classification. Unsupervised classification algorithms like the one deployed by [1]} can be a good starting point to explore this question.
